Our long-range objective is to understand the functional organization and dynamical activity of the cortex. The discovery of the columnar organization of the cortex has led to the notion that the columns are fundamental building blocks, from which larger functional units are constructed. The cortex is thus viewed as a crystal (a more or less regular array of repeating, similar modules. Our proposal will test and refine this modular hypothesis. We shall use optical imaging of the primary visual cortex of monkeys and cats, and simultaneously record electrical responses from small neuronal clusters and local field potentials. We shall thus obtain a spatio- temporal picture of the activity in the neural ensembles which encode various stimulus parameters. The data will be analyzed with extensions of Principal Component Analysis that we have developed. We address three major aims: 1) To test the modularity hypothesis we shall measure, in a large piece of cortical tissue, the full range of functional maps ( for orientation, color, spatial frequency etc.) together with the retinotopic map. We shall measure the periodicity of, and correlations among, the functional maps, to determine if they are commensurate. This will lead to a refined framework that could include possibly incommensurate cortical scales and interactions among cortical elements. 2) We shall investigate how the Principal Components (eigenfunctions) obtained from the optical images depend on the extent of the visual stimulus, to determine how the dynamical dimension of the primary visual cortex (viewed as a dynamical system) scales with size. 3) We shall study the concerted electrical responses of neuronal clusters, to clarify the link between optical signals and neuronal activity, and to deepen our understanding of the neuronal dynamics. Our study is aimed at an intermediate architectural level, and deals with the way in which the fundamental modalities of the visual world (orientation, size, color and so on) are analyzed in the primary visual cortex. Such knowledge is crucial for the construction of cortical models, which are essential for any quantitative understanding of critical function and dysfunction.